Senior Manager - NGS

Why join Freenome?

Freenome is a high-growth biotech company on a mission since 2014 to create tools that empower everyone to prevent, detect, and treat their disease. 

To achieve this mission, Freenome is developing next-generation blood tests to detect cancer in its earliest, most treatable stages using our multiomics platform and machine learning techniques. Our first blood test will detect early-stage colorectal cancer and advanced adenomas.

To fight the war on cancer, Freenome has raised more than $1.1B from leading investors including a16z, GV (formerly Google Ventures), T. Rowe Price, BainCapital, Perceptive Advisors, RA Capital Management, Roche, Kaiser Permanente Ventures, and the American Cancer Society’s BrightEdge Ventures. 

Are you ready for the fight? A ‘Freenomer’ is a mission-driven employee who is fueled by the opportunity to make a positive impact on patients' lives, who thrive in a culture of respect and cross collaboration, and whose work makes a significant impact on the company and their career. Freenomers are determined, patient-centric, and outcomes-driven. We build teams around divergent expertise, allowing us to solve problems and ascertain opportunities in unique ways. We are dedicated to advancing healthcare, one breakthrough at a time.

About this opportunity:

At Freenome, our goal is to improve patient outcomes by pioneering the next-generation of blood tests for early and accurate disease detection using our combined multi-omics and machine learning platform. As a Senior Manager in Genomics, you will contribute to the program’s technical base by creating and optimizing new next-generation sequencing (NGS) assays and workflows for DNA/RNA, or to the program’s scientific base by elevating our understanding of the biological context of these assay signals in cancer. In this role, you will lead projects to evaluate emergent technologies that have the potential to improve our diagnostic tests, collect and analyze NGS datasets (including genomics, epigenomics, and transcriptomics) for biomarker discovery, and augment existing multi-omic models with novel signals you discover. You will also work closely with computational biologists and machine learning scientists to provide biological and technical insights, and to provide new data sources to enhance ongoing computational research projects.

What you’ll do:

• Apply fundamental understanding of molecular biology, nucleic-acid biochemistry, and NGS to develop new molecular assays that span both genome-wide and targeted strategies.
• Stay at the cutting edge of NGS methodology to identify and evaluate new technologies to improve our multi-omics capabilities.
• Refine and optimize existing NGS assays by characterizing assay performance and implementing workflow and protocol improvements (including nucleic acid extraction, library preparation, and downstream analysis).
• Investigate the biological origin of blood-based biomarkers by performing detailed characterization of cell-free material, tumors, and the immune system. 
• Drive biomarker discovery studies that leverage both in-house generated datasets and published reference databases.
• Collaborate with computational biologists and software engineers to build analysis pipelines that appropriately integrate new molecular technologies.
• Lead projects spanning molecular and computational functions to better understand the underlying biology of non-invasive cancer biomarkers.
• Manage 1-3 junior scientists or research associates, helping them grow and contribute to our mission.

Must haves:

• PhD (or equivalent industry experience) in molecular biology, biochemistry, genetics, cancer biology, immunology, or a related field.
• 7+ years post-PhD experience in NGS assays (for Staff-level Research Scientist).
• Proven track record of implementing new methods for NGS-based protocols that go beyond commercially available kits.
• Ability to perform NGS data analysis to enable experimental iteration independent of external support.
• Clear communication skills with an ability to clearly communicate across diverse audiences with a range of technical knowledge
• Demonstrated ability to lead cross-functional collaborations, including team members in the same and adjacent disciplines.
• Deep understanding of cancer biology and experience working with cancer genomics datasets to interrogate molecular mechanisms (e.g., TCGA)
• Experience managing, mentoring, and training junior scientists or research associates.

Nice to haves:

• Experience with methods for DNA methylation analysis (e.g., bisulfite sequencing), leading to successful publication, patent filing, funding, or other project completion milestones.
• Fluency in a common scientific programming language (e.g., Python or R).
• Experience working with liquid handling platforms for high-throughput research projects.

Benefits and additional information:

The US target range of our base salary rate for new hires is $165,750 - $225,000. You will also be eligible to receive pre-IPO equity, cash bonuses, and a full range of medical, financial, and other benefits dependent on the position offered.  Please note that individual total compensation for this position will be determined at the Company’s sole discretion and may vary based on several factors, including but not limited to, location, skill level, years and depth of relevant experience, and education. We invite you to check out our career page @ https://careers.freenome.com/ for additional company information.  

Freenome is proud to be an equal opportunity employer and we value diversity. Freenome does not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, veteran status, or any other status protected under federal, state, or local law.

Applicants have rights under Federal Employment Laws.  

• Family & Medical Leave Act (FMLA)
• Equal Employment Opportunity (EEO)
• Employee Polygraph Protection Act (EPPA)

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